Generative deep learning models are artificial intelligence (AI) systems that can create texts, images, audio files, and videos for specific purposes, following instructions provided by human users.

From fine-tuning open source models to building agentic frameworks on top of them, the open source world is ripe with ...

The rise of AI has given us an entirely new vocabulary. Here's a list of the top AI terms you need to learn, in alphabetical order.

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...

Abstract: Energy Internet and system integration promote the development of green energy, but the battery recycling problem is becoming increasingly serious, especially the proliferation of used ...

Following the sequence and structure revolutions, predicting functionally relevant protein structure changes at scale remains an outstanding challenge. We introduce BioEmu, a deep learning system that ...

DR Tulu-8B is the first open Deep Research (DR) model trained for long-form DR tasks. DR Tulu-8B matches OpenAI DR on long-form DR benchmarks. agent/: Agent library (dr-agent-lib) with MCP-based tool ...

Abstract: Significant advancements in deep learning have been made possible by the utilization of large datasets, underscoring the critical importance of copyright protection. Adding meticulously ...

📣 vLLM x Triton Meetup at Fort Mason on Sept 9th 4:00 - 9:00 pm We are excited to announce that we will be hosting our Triton user meetup with the vLLM team at Fort Mason on Sept 9th 4:00 - 9:00 pm.

Artificial intelligence models can secretly transmit dangerous inclinations to one another like a contagion, a recent study found. Experiments showed that an AI model that’s training other models can ...

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...

Background: Diabetic retinopathy (DR) screening faces critical challenges in early detection due to its asymptomatic onset and the limitations of conventional prediction models. While existing studies ...